All Peacekeeping is Local: Measuring Subnational Variation in Peacekeeping Effectiveness

TY - JOUR

T1 - All Peacekeeping is Local

T2 - Measuring Subnational Variation in Peacekeeping Effectiveness

AU - Reeder, Bryce

AU - Hendricks, Michael

AU - Goldring, Edward Peter Alan

N1 - © The Author(s) (2022). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2022/5/7

Y1 - 2022/5/7

N2 - Understanding whether peacekeepers reduce fatalities at the local level is an important question. We can have increased confidence in peacekeepers’ capabilities by testing whether deaths decrease in the locations where peacekeepers are present. However, commonly used modeling techniques cannot easily test peacekeepers’ local effectiveness. Coefficients from methods such as linear regression, logit, and count models provide average estimates of peacekeepers’ effects on violence. We argue that a solution lies in geographically weighted regression (GWR). GWR can more clearly reveal subnational spatial heterogeneity in peacekeepers’ (in)effectiveness at reducing violence. We conduct an illustrative test of our argument using data on the Democratic Republic of the Congo between 2001 and 2014 and replicate an existing study to show that GWR can also help resolve seemingly contradictory findings of whether peacekeepers are better at reducing violence by government or rebel actors. The article contains important implications for how scholars can more accurately measure peacekeeping effectiveness.

AB - Understanding whether peacekeepers reduce fatalities at the local level is an important question. We can have increased confidence in peacekeepers’ capabilities by testing whether deaths decrease in the locations where peacekeepers are present. However, commonly used modeling techniques cannot easily test peacekeepers’ local effectiveness. Coefficients from methods such as linear regression, logit, and count models provide average estimates of peacekeepers’ effects on violence. We argue that a solution lies in geographically weighted regression (GWR). GWR can more clearly reveal subnational spatial heterogeneity in peacekeepers’ (in)effectiveness at reducing violence. We conduct an illustrative test of our argument using data on the Democratic Republic of the Congo between 2001 and 2014 and replicate an existing study to show that GWR can also help resolve seemingly contradictory findings of whether peacekeepers are better at reducing violence by government or rebel actors. The article contains important implications for how scholars can more accurately measure peacekeeping effectiveness.

U2 - 10.1093/isq/sqac010

DO - 10.1093/isq/sqac010

M3 - Article

SN - 1468-2478

VL - 66

JO - International Studies Quarterly

JF - International Studies Quarterly

IS - 2

M1 - sqac010

ER -